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Technology · QAVE

Evaluate every AI system before you trust it.

QAVE helps Qapitol evaluate AI systems, agents and outputs at scale — so enterprises know what behaves correctly, what fails, and what cannot be signed off.

QAVE evaluating AI systems at scale
Customer-facing chatbotLLM · output evaluationCAN'T SIGN OFFRAG knowledge assistantRAG · response validationCAN'T SIGN OFFAgent workflowPrompt + behaviour testingSIGNED OFFContent generation modelSafety + hallucination checksCAN'T SIGN OFF

Every AI system is scored against the eval dimensions — and either clears the sign-off threshold or gets sent back. Illustrative; not a measured result.

Why evaluation, not testing

AI doesn’t fail like software.

AI systems can’t be validated with ordinary test cases. They generate variable outputs, behave differently across prompts and contexts, and fail in ways traditional QA can’t predict. QAVE evaluates them the way they actually behave — at scale — so you know what’s correct, what fails, and what cannot be signed off.

What it evaluates

The suites that make a system signable.

Each suite answers a different question about how an AI system behaves. Run together, they turn a model you can only hope about into one you can put a verdict on.

LLM output evaluation

Judge what a model actually returns — not just whether the call succeeded.

RAG response validation

Test retrieval-grounded answers for accuracy before they reach a user.

Prompt + behaviour testing

See how a system behaves across prompts and contexts, not one happy path.

Safety + hallucination checks

Surface unsafe, fabricated or off-policy output before it ships.

Domain-specific scoring rubrics

Score against what “correct” means for your domain, not a generic metric.

Regression evaluation for AI systems

Catch quality drift when a model, prompt or dataset changes.

Human + AI evaluation workflows

Combine automated scoring with human judgement where it counts.

Where it fits

The evidence behind sign-off.

QAVE powers the Evaluate and Verify stages of the Qapitol Control Layer — the point where an AI system stops being a black box and starts producing the evidence a sign-off needs. See the full control layer →

  • Validate a customer-facing chatbot
  • Test RAG accuracy before release
  • Benchmark multiple LLMs
  • Build repeatable eval suites
  • Produce AI Sign-Off evidence

Want to know which AI systems can be signed off?

Start with an AI Exposure Snapshot, or talk to us about your specific situation.